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Desi R Ivanova

@desirivanova.bsky.social
4.5K followers 222 following 64 posts

Research fellow @OxfordStats @OxCSML, spent time at FAIR and MSR Former quant 📈 (@GoldmanSachs), former former gymnast 🤸‍♀️ My opinions are my own 🇧🇬-🇬🇧 sh/ssh

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Reposted by Desi R Ivanova
Department of Statistics @oxfordstatistics.bsky.social · 07/04/2025
🏢 Vacancy: Novo Nordisk Postdoctoral Research Fellow (4 posts) 📍 Department of Statistics, University of Oxford 📃 Contract: Full time, fixed-term for 3 years 💷 Salary Range: £36,024 – £44,263 ⏲️ Deadline: 12pm UK, 30 Apr 2025 Full details & how to apply 👉 shorturl.at/3l47e
shorturl.at
Job Details
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Desi R Ivanova @desirivanova.bsky.social · 07/04/2025
Research internships in AI safety www.lasrlabs.org
lasrlabs.org
LASR Labs
Join a 13-week research programme and write a technical AI safety paper in a small team with supervision from an experienced researcher. Work full time from the LISA offices in London alongside AI Saf...
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Desi R Ivanova @desirivanova.bsky.social · 17/03/2025
Last DL lecture open.substack.com/pub/probappr...
open.substack.com
Lecture 6: Training practicalities
Deep learning's black magic
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Desi R Ivanova @desirivanova.bsky.social · 12/03/2025
Lecture 5: Backpropagation and Autodifferentiation Thank god the days of computing gradients by hand are over! Nevertheless, it’s good to know what backprop is and why we do it open.substack.com/pub/probappr...
open.substack.com
Lecture 5: Backprop and Autodiff
Order matters
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Desi R Ivanova @desirivanova.bsky.social · 09/03/2025
The fourth post in the series: open.substack.com/pub/probappr...
open.substack.com
Lecture 4: Neural network architectures
Attention!
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
Go read it on arXiv! Thanks to my co-authors @sambowyer.bsky.social and @laurenceai.bsky.social 💥
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
Along with the lightweight library, we provide short code snippets in the paper.
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
…and for constructing error bars on more complicated metrics, such as F1 score, that require the flexibility of Bayes.
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
...and treated without an independence assumption (e.g. using the same eval questions on both LLMs)...
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
...for making comparisons between two LLMs treated independently...
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
We also suggest simple methods for the clustered-question setting (where we don't assume all questions are IID -- instead we have T groups of N/T IID questions)...
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
Or, in this IID question setting, if you want to stay frequentist you can use Wilson-score intervals: en.wikipedia.org/wiki/Binomial_…
en.wikipedia.org
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
We suggest using Bayesian credible intervals for your error bars instead, with a simple Beta-Binomial model. (The aim is for the methods to achieve nominal 1-alpha coverage i.e. match the dotted line in the top row. A 95% confidence interval should be right 95% of the time.)
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
This, along with the CLT's ignorance of typically binary eval data (correct/incorrect responses to an eval question) lead to poor error bars which collapse to zero-width or extend past [0,1].
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
As LLMs get better, benchmarks to evaluate their capabilities are getting smaller (and harder). This starts to violate the CLT's large N assumption. Meanwhile, we have lots of eval settings in which questions aren't IID (e.g. questions in a benchmark often aren't independent).
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Desi R Ivanova @desirivanova.bsky.social · 06/03/2025
Our paper on the best way to add error bars to LLM evals is on arXiv! TL;DR: Avoid the Central Limit Theorem -- there are better, simple Bayesian and frequentist methods you should be using instead. We also provide a super lightweight library: github.com/sambowyer/baye… 🧵👇
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Desi R Ivanova @desirivanova.bsky.social · 03/03/2025
The third in the teaching blogs series: Introduction to deep learning open.substack.com/pub/probappr...
open.substack.com
Lecture 3: Introduction to Deep Learning
aka neural networks aka differentiable programming
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Desi R Ivanova @desirivanova.bsky.social · 26/02/2025
NHS boss was sacked (well, “resigned”), so there’s some hope for major reforms and improvements in the health system (I hope 🤞)
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Desi R Ivanova @desirivanova.bsky.social · 25/02/2025
open.substack.com/pub/probappr...
open.substack.com
Lecture 2: Marginal likelihood, non-Gaussian likelihoods and... scalability issues
Things might not be nice and easy even when everything is Gaussian
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Reposted by Desi R Ivanova
Nathan Lambert @natolambert.bsky.social · 25/02/2025
Come work with me! We are looking to bring on more top talent to our language modeling workstream at @ai2.bsky.social building the open ecosystem. We are hiring: * Research scientists * Senior research engineers * Post docs (Young investigators) * Pre docs job-boards.greenhouse.io/thealleninst...
job-boards.greenhouse.io
The Allen Institute for AI
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
Nice. Are the materials publicly available?
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
We currently do 2 lectures on GPs 😅 one could certainly do a whole course (bayesopt, automl) - could be fun!
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
Indeed, the course is already really quite tight. So if DPs are to be covered, something has to be dropped. I’m thinking for next year potentially dropping constrained optimisation/SVMs (done in the first half) and covering BNP more thoroughly
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
It’s a mix - first part was ERM, SVMs and kernels; second part (which is the one I’m teaching) - Bayesian ML (GPs), deep learning and VI
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
Teaching is super undervalued by universities (at least in UK) so there’s very little incentive to do it well. I think this is wrong and thoughtful pedagogy matters deeply. I hope these “teaching blogs” series will help me get up to speed and improve more quickly open.substack.com/pub/probappr...
open.substack.com
Lecture 1: Gaussian Processes and GP Regression
Nice and easy when everything is Gaussian
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Desi R Ivanova @desirivanova.bsky.social · 21/02/2025
I’m teaching a grad course for the first time (a bit terrifying 😅) and I’ve decided to write a short blog post after each lecture, that will highlight a key takeaway from it and reflect on what can be improved. First one ⬇️
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Reposted by Desi R Ivanova
Desi R Ivanova @desirivanova.bsky.social · 12/02/2025
📣 Jobs alert We’re hiring postdoc and research engineer to work on UQ for LLMs!! Details ⬇️ #ai #llm #uq
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Desi R Ivanova @desirivanova.bsky.social · 12/02/2025
📣 Jobs alert We’re hiring postdoc and research engineer to work on UQ for LLMs!! Details ⬇️ #ai #llm #uq
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Desi R Ivanova @desirivanova.bsky.social · 08/02/2025
A tiny "embers of autoregression" artifact in simple arithmetic probapproxincorrect.substack.com/p/embers-of-au…
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Reposted by Desi R Ivanova
Department of Statistics @oxfordstatistics.bsky.social · 06/02/2025
🌟 Research Collaboration Morning 🌟 Our recent Research Collaboration Morning featured talks from Hrushi Loya (SGBE) & @desirivanova.bsky.social (CSML) over tea & coffee, followed by amazing treats from Waste2Taste & Blakes Food. Thanks to Prof Simon Myers and Bev Lane for organising!
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Desi R Ivanova @desirivanova.bsky.social · 18/01/2025
Congrats Tim 🔥
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Reposted by Desi R Ivanova
Brandon Amos @bdamos.bsky.social · 06/01/2025
📢 My team at Meta (including Yaron Lipman and Ricky Chen) is hiring a postdoctoral researcher to help us build the next generation of flow, transport, and diffusion models! Please apply here and message me: www.metacareers.com/jobs/1459691...
metacareers.com
Postdoctoral Researcher, Fundamental AI Research (PhD)
Meta's mission is to build the future of human connection and the technology that makes it possible.
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Reposted by Desi R Ivanova
Andrew Gordon Wilson @andrewgwils.bsky.social · 03/01/2025
We're excited to announce the ICML 2025 call for workshops! The CFP and submission advice can be found at: icml.cc/Conferences/.... The deadline is Feb 10. Submit some creative proposals!
icml.cc
ICML 2025 Call for Workshops
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Reposted by Desi R Ivanova
Ben Golub @bengolub.bsky.social · 24/12/2024
It also makes for a bad equilibrium where publicly disagreeing with a paper (except very mildly and boringly) is infrequent and therefore an extreme signal. So people don't do it even when they feel published papers are wrong or misleading. 3/
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Desi R Ivanova @desirivanova.bsky.social · 23/12/2024
Overall, 0 rates were great for the progress in AI. High rates are great for making commercial products, but that naturally means “fundamental research” is no longer a priority. Such cycles are a good thing
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Desi R Ivanova @desirivanova.bsky.social · 23/12/2024
IMO these jobs existed as a consequence of money being free. It is not a coincidence that OAI started pushing for monetisable products shortly after rates started going up (March 2022, chatgpt was released in Nov).
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Desi R Ivanova @desirivanova.bsky.social · 23/12/2024
Being able to do “academic research” at a tech salary was a zero interest rate phenomenon
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Reposted by Desi R Ivanova
Razvan Pascanu @razvan-pascanu.bsky.social · 15/12/2024
For my first post on Bluesky .. I'll start by announcing our 2025 edition of EEML which will be in Sarajevo :) ! I'm really excited about it and hope to see many of you there. Please follow the website (and Bluesky account) for more details which are coming soon ..
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Desi R Ivanova @desirivanova.bsky.social · 13/12/2024
The news is finally out: Ellison Institute of Technology (EIT) is opening a campus in Oxford 💥 The Foundations of AI is an EIT+Oxford programme - more details here www.eitcdt.ox.ac.uk/foaicdt
eitcdt.ox.ac.uk
Home
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Reposted by Desi R Ivanova
Marvin Schmitt @marvin-schmitt.com · 11/12/2024
cool now do this bsky.app/profile/labu...
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Desi R Ivanova @desirivanova.bsky.social · 11/12/2024
Could this (at least to an extent) be due to the fact that big tech labs no longer publish this sort of research?
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Desi R Ivanova @desirivanova.bsky.social · 11/12/2024
I guess I could start a side hustle providing gymnastics training data for video models
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Desi R Ivanova @desirivanova.bsky.social · 11/12/2024
😂
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Desi R Ivanova @desirivanova.bsky.social · 08/12/2024
✨✨
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Desi R Ivanova @desirivanova.bsky.social · 29/11/2024
It’s hot takes Friday 😅 probapproxincorrect.substack.com/p/some-thoug...
probapproxincorrect.substack.com
Some thoughts on the role of Bayesianism in the age of Modern AI
It works because it works.
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Desi R Ivanova @desirivanova.bsky.social · 27/11/2024
Any way, there might be something clever in the implementation details that’s not in the paper, so I’m also very much looking forward to the release 🙃
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Desi R Ivanova @desirivanova.bsky.social · 27/11/2024
Nice (I’ve bookedmarked the table to look at) Definitely agree on the need for robust verification! But I’m not sure if GSM-Symbolic solves that (they do verify 10 out of 100 samples manually but don’t say how that’s used for quality control, there’s no stats around how many “failed” etc)
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Desi R Ivanova @desirivanova.bsky.social · 26/11/2024
I haven’t looked into it in a lot of detail, but I think templateGSM does a very similar thing to GSM symbolic huggingface.co/datasets/mat...
huggingface.co
math-ai/TemplateGSM · Datasets at Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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Paul Bürkner @paulbuerkner.com · 26/11/2024
Prior specification is one of the hardest tasks in Bayesian modeling. In our new paper, we (Florence Bockting, @stefanradev.bsky.social and me) develop a method for expert prior elicitation using generative neural networks and simulation-based learning. arxiv.org/abs/2411.15826
arxiv.org
Expert-elicitation method for non-parametric joint priors using normalizing flows
We propose an expert-elicitation method for learning non-parametric joint prior distributions using normalizing flows. Normalizing flows are a class of generative models that enable exact, single-step...
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